code: def test_predict_proba_large_n_classes(datatype):
      nrows = 10000
      ncols = 100
      n_neighbors = 10
      n_clusters = 10000
  
      X, y = make_blobs(
          n_samples=nrows,
          centers=n_clusters,
          n_features=ncols,
          cluster_std=0.01,
          random_state=0,
      )
  
      X = X.astype(np.float32)
  
      X_train, X_test, y_train, y_test = _build_train_test_data(
          X, y, datatype
      )
  
      knn_cu = cuKNN(n_neighbors=n_neighbors)
      knn_cu.fit(X_train, y_train)
  
      predictions = knn_cu.predict_proba(X_test)
  
      if datatype == "dataframe":
          predictions = predictions.to_numpy()
  
      assert np.rint(np.sum(predictions)) == len(y_test)
  
file_path: cuml/python/cuml/tests/test_kneighbors_classifier.py
imports: from cuml.testing.utils import array_equal
  from cuml.internals.safe_imports import cpu_only_import
  from sklearn.datasets import make_blobs
  from sklearn.neighbors import KNeighborsClassifier
  from cuml.neighbors import KNeighborsClassifier
  import cuml
  import pytest
  from cuml.internals.safe_imports import gpu_only_import
label_desc: Use image node_id 5 for calling a global function with example usage: test_predict_proba_large_n_classes(datatype) without return types